scholarly journals ANALISA DAN PERANCANGAN CHECK-AP : APLIKASI PEMERIKSAAN KESEHATAN ANAK DENGAN FITUR FACE DETECTOR

2019 ◽  
Vol 1 (1) ◽  
pp. 25-28
Author(s):  
Enggarbela Ogi Intan Pratiwi ◽  
Abdul Khamid ◽  
Fitria Hidayanti ◽  
Salamun Rohman Nudin
Keyword(s):  
Face Recognition ◽  
Face Detector

Penulisan artikel ilmiah ini bertujuan untuk memaparkan pemanfaatan fitur face detector yang ada pada handphone yang dapat digunakan untuk melakukan pemeriksaan kesehatan pada anak serta dengan memanfaatkan fitur face recognition untuk mengenali wajah dan melakukan pemindaian wajah serta mengenali gejala penyakit yang dapat dilihat melalui wajah supaya aplikasi ini dapat mendeteksi penyakit yang ada pada anak. “Check-Ap”merupakan sebuah aplikasi yang digunakan untuk melakukan pemeriksaan kesehatan anak untuk mendapatkan hasil diagnosis terkini penyakit anak sebelum melakukan pemeriksaan lanjutan dengan dokter spesialis anak. Seiring dengan pengembangan ”Check-Ap”, diharapkan nantinya aplikasi ini dapat membantu para orang tua serta mampu untuk menolong jutaan nyawa anak-anak di Indonesia sehingga mampu menurunkan angka kematian anak setiap tahunnya.

A Low-Power Convolutional Neural Network Face Recognition Processor and a CIS Integrated With Always-on Face Detector

2018 ◽  
Vol 53 (1) ◽  
pp. 115-123 ◽  
Author(s):  
Kyeongryeol Bong ◽  
Sungpill Choi ◽  
Changhyeon Kim ◽  
Donghyeon Han ◽  
Hoi-Jun Yoo
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Low Power ◽  
Convolutional Neural Network ◽  
Face Detector

FPLP3D: Security robot for face recognition in the workplace environment using face pose detection assisted controlled FACE++ tool position: A three-dimensional robot

Work ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 881-890
Author(s):  
Meifeng Han ◽  
Fuli Zhang ◽  
Ning Ning ◽  
Junwei Zhou ◽  
A. Shanthini ◽  
...  
Keyword(s):  
Face Recognition ◽  
Three Dimensional ◽  
Workplace Environment ◽  
3 Dimensional ◽  
Pose Detection ◽  
Real Video ◽  
Tool Position ◽  
Conventional Systems ◽  
Single Sequence ◽  
Face Detector

BACKGROUND: In recent years, several tracker systems have been developed to monitor a 3-dimensional skull position for facial action whereas, various tracker systems simultaneously analyze the single sequence of video, which can be provided with low-quality cameras and less security. Initially, implementing a 2-D face detector and an unrepentance system has been suggested; furthermore, it has been improved using an integrated 3-D face initialized scheme for the real-time tracker in the present face recognition systems. OBJECTIVES: To overcome the present setbacks of the conventional systems, Face Pose Detection assisted controlled FACE++ tool position of Three-Dimensional Robot (FPLF3D) has been proposed in this article. Furthermore, the suggested proposed configuration has a high-end monitoring approach, which is used to improve the reliability of the robot’s human-machine contact in the workplace environment for security assistance. Additionally, the robot’s direction can be controlled by the operator’s head position assessment of the camera (or any active viewing system) using a three-dimensional robot. RESULTS: Besides, the applications that are imitated by headers like telepresence, computer-generated reality, and video competitions will directly take advantage of the strategies introduced in this paper. CONCLUSION: Finally, real video tests at the lab-scale level show the accuracy and usefulness of the approaches proposed in this research outperform the existing methods used for tracking.

scholarly journals Real Time Face Recognition using Eigenface and Viola-Jones Face Detector

2017 ◽  
Vol 1 (1) ◽  
pp. 16 ◽  
Author(s):  
Jacky Efendi ◽  
Muhammad Ihsan Zul ◽  
Wawan Yunanto
Keyword(s):  
Face Recognition ◽  
Light Intensity ◽  
Real Time ◽  
Face Image ◽  
Recognition Time ◽  
Final Project ◽  
Face Images ◽  
Input Face ◽  
The Subject ◽  
Face Detector

Authentication is the process of verifying one’s identity, and one of its implementation is in taking attendances in university’s lectures. Attendance taking is a very important matter to every academic institution as a way to examine students’ performance. Signature based attendance taking can be manipulated. Therefore it has problems in verifying the attendance validity. In this final project, a real time eigenface based face recognition is implemented in an application to do attendance taking. The input face image is captured using a webcam. The application itself is built in C#, utilizing EmguCV library. The application is developed using Visual Studio 2015. Face detection is done with Viola-Jones algorithm. The eigenface method is used to do facial recognition on the detected face image. In this final project, a total of 8 testings are done in different conditions. From the testings, it is found that this application can recognize face images with accuracy as high as 90% and as low as 6.67%. This solution can be used as an alternative for real-time attendance taking in an environment with 170 lux light intensity, webcam resolution of 320 x 240 pixel, and the subject standing 1 meter away while not wearing spectacles. The average recognition time is 0.18125 ms.

scholarly journals Performance Analysis of Face Detection system using HOG and QualHOG Features

2019 ◽  
Vol 8 (6) ◽  
pp. 2079-2083
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Cell Phones ◽  
Perceptual Quality ◽  
Picture Quality ◽  
Speed Distribution ◽  
Face Location ◽  
The Face ◽  
Minimal Effort ◽  
Face Detector

Inspired by the expansion of minimal effort advanced cameras in cell phones being conveyed in computerized systems, we think about the connection between perceptual picture quality and an exemplary PC vision errand of face recognition. We measure the corruption in execution of a well known and compelling face detector when human-saw image quality is corrupted by twists usually happening in catch, stockpiling, and transmission of facial pictures, including clamor, obscure, and pressure. It is observed that, inside a certain scope of picture quality, an unobtrusive increment in picture quality can radically enhance face recognition execution. These outcomes can be utilized to guide asset or transfer speed distribution in securing or correspondence/conveyance frameworks that are connected with face location undertakings. In this work a perceptual quality QualHOG feature is used. Face locators prepared on these new components give measurably huge change in resilience to picture bends over a solid gauge. Distortion dependent which is more distorted uninformed variations of the face indicators are proposed and assessed on a huge database of face pictures speaking to an extensive variety of mutilations. A one-sided variation of the preparing calculation is additionally recommended that further improves the power of these face locators. To encourage this exploration, we have developed another dataset in our lab for further study.

Face Inversion Effect Emerges Under Critical Configural Discrepancy

2010 ◽  
Vol 69 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Jisien Yang ◽  
Adrian Schwaninger
Keyword(s):  
Face Recognition ◽  
Face Processing ◽  
Underlying Mechanism ◽  
Inversion Effect ◽  
Configural Processing ◽  
Major Contributor ◽  
Face Inversion Effect ◽  
Configural Information ◽  
Face Inversion ◽  
The Face

Configural processing has been considered the major contributor to the face inversion effect (FIE) in face recognition. However, most researchers have only obtained the FIE with one specific ratio of configural alteration. It remains unclear whether the ratio of configural alteration itself can mediate the occurrence of the FIE. We aimed to clarify this issue by manipulating the configural information parametrically using six different ratios, ranging from 4% to 24%. Participants were asked to judge whether a pair of faces were entirely identical or different. The paired faces that were to be compared were presented either simultaneously (Experiment 1) or sequentially (Experiment 2). Both experiments revealed that the FIE was observed only when the ratio of configural alteration was in the intermediate range. These results indicate that even though the FIE has been frequently adopted as an index to examine the underlying mechanism of face processing, the emergence of the FIE is not robust with any configural alteration but dependent on the ratio of configural alteration.

Perceptual Effects and Recollective Experience in Face Recognition

2005 ◽  
Vol 52 (3) ◽  
pp. 224-231 ◽  
Author(s):  
Chrisanthi Nega
Keyword(s):  
Face Recognition ◽  
Recognition Memory ◽  
Congruency Effect ◽  
Facial Recognition ◽  
Memory Systems ◽  
Study Time ◽  
Perceptual Fluency ◽  
Recollective Experience ◽  
Trace Strength ◽  
Size Congruency

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.

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